286 search results - page 19 / 58 » Learning to Classify Texts Using Positive and Unlabeled Data |
AAAI
2004
13 years 9 months ago
2004
Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
IRAL
2003
ACM
14 years 25 days ago
2003
ACM
Namedentityrecognition isimportantinsophisticatedinformation service system such as Question Answering and Text Mining since most of the answer type and text mining unit depend on...
SAC
2004
ACM
14 years 1 months ago
2004
ACM
The importance of text mining stems from the availability of huge volumes of text databases holding a wealth of valuable information that needs to be mined. Text categorization is...
SDM
2008
SIAM
13 years 9 months ago
2008
SIAM
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
MLDM
2005
Springer
14 years 1 months ago
2005
Springer
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...